The Science Of A Supermodel

The right timing, personality, and, of course, looks go into creating a supermodel - but a new study suggests that the rise of a new fashion star is not as random as it seems.

Researchers from the Indiana University School of Informatics and Computing looked at "the social and professional determinants of success in the fashion industry" to find who the coming season's catwalk star would be - and, unlike many areas of mathematics, this is one formula we can wrap our heads round easily. Which is no surprise since this formula is called "The Kendall Jenner Effect".

Between September and December 2014, the school's research assistant professor, Emilio Ferrara, and his team counted how many Instagram posts a range of top models did, and assessed how many likes and comments each post got on average. Then, using the Fashion Model Directory, they aggregated portfolio data - including how many times they had appeared on the catwalk so far, as well as other statistics including their height and shoe size. This information was then fed into multiple algorithms, which enabled the team to predict how "popular" the model would be at the forthcoming fashion month - as defined by how many catwalks she would appear on - with 80 per cent accuracy.

What the researchers perhaps didn't take into account, which New York Magazine also notes, is that walking the maximum number of catwalk shows is not necessarily a measure of supermodel status and, in fact, once a model gets to the point when she only has to walk in a few shows, for a few choice brands - in the way that Cara Delevingne, Karlie Kloss, and (until recently) Gisele Bündchen have done - that is the true measure of supermodel success.